The Integration and Abstracyion of EBS Models in Yucca Mountain Performance Assessment

The safety strategy for geological disposal of radioactive waste at Yucca Mountain relies on a multi-barrier system to contain the waste and isolate it from the biosphere. The multi-barrier system consists of the natural barrier provided by the geological setting and the engineered barrier system (EBS). In the case of Yucca Mountain (YM) the geologic setting is the unsaturated-zone host rock, consisting of about 600 meters of layered ash-flow volcanic tuffs above the water table, and the saturated zone beneath the water table. Both the unsaturated and saturated rocks are part of a closed hydrologic basin in a desert surface environment. The waste is to be buried about halfway between the desert surface and the water table. The primary engineered barriers at YM consist of metal components that are highly durable in an oxidizing environment. The two primary components of the engineered barrier system are highly corrosion-resistant metal waste packages, made from a nickel-chromium-molybdenum alloy, Alloy 22, and titanium drip shields that protect the waste packages from corrosive dripping water and falling rocks. Design and performance assessment of the EBS requires models that describe how the EBS and near field behave under anticipated repository-relevant conditions. These models must describe coupled hydrologic, thermal, chemical, and mechanical (THCM) processes that drive radionuclide transport in a highly fractured host rock, consisting of a relatively permeable network of conductive fractures in a setting of highly impermeable tuff rock matrix. An integrated performance assessment of the EBS must include a quantification of the uncertainties that arise from (1) incomplete understanding of processes and (2) from lack of data representative of the large spatial scales and long time scales relevant to radioactive waste disposal (e.g., long-term metal corrosion rates and heterogeneities in rock properties over the large 5 km{sup 2} emplacement area of the repository). A systematic approach to EBS model development and performance assessment should include as key elements: (1) implementation of a systematic FEPs approach, (2) quantification of uncertainty and variability, (3) sensitivity analyses, and (4) model validation and limitations. The approaches used for these key elements in the Yucca Mountain repository program are described in Section 2 of this paper. A specific example of Yucca Mountain EBS model development and integration, related to the modeling of localized corrosion of Alloy 22, is discussed in Sections 3 and 4

Total System Performance Predictions (TSPA-1995) for the Potential High-Level Waste Repository at Yucca Mountain

The management and operating contractor for the potential high-level nuclear waste repository at Yucca Mountain, Nevada, has been recently completed a new performance assessment of the ability of the repository to isolate and contain nuclear waste for long time periods (up to 1,000,000 years). Sensitivity analyses determine the most important physical parameters and processes, using the most current information and models

SUPPLEMENTAL PERFORMANCE ANALYSES FOR THE POTENTIAL HIGH-LEVEL NUCLEAR WASTE REPOSITORY AT YUCCA MOUNTAIN

ABSTRACT The U.S. Department of Energy (DOE) is considering the possible recommendation of a site at Yucca Mountain, Nevada, for the potential development of a geologic repository for the disposal of high-level radioactive waste and spent nuclear fuel. To facilitate public review and comment, in May 2001 the DOE released the Yucca Mountain Science and Engineering Report (S&ER) (1), which presents technical information supporting the consideration of the possible site recommendation. The report summarizes the results of more than 20 years of scientific and engineering studies. Based on internal reviews of the S&ER and its key supporting references, the Total System Performance Assessment for the Site Recommendation (TSPA-SR) (2) and the Analysis Model Reports and Process Model Reports cited therein, the DOE has recently identified and performed several types of analyses to supplement the treatment of uncertainty in support of the consideration of a possible site recommendation. The results of these new analyses are summarized in the two-volume report entitled FY01 Supplemental Science and Performance Analysis (SSPA) (3,4). The information in this report is intended to supplement, not supplant, the information contained in the S&ER. The DOE recognizes that important uncertainties will always remain in any assessment of the performance of a potential repository over thousands of years (1). One part of the DOE approach to recognizing and managing these uncertainties is a commitment to continued testing and analysis and to the continued evaluation of the technical basis supporting the possible recommendation of the site, such as the analysis contained in the SSPA. The goals of the work described here are to provide insights into the implications of newly quantified uncertainties, updated science, and evaluations of lower operating temperatures on the performance of a potential Yucca Mountain repository and to increase confidence in the results of the TSPA described in the S&ER (1). The primary tool used to evaluate the implications of the three types of supplemental information described in the SSPA (3,4) is the Yucca Mountain integrated TSPA model. WM '02 Conference, February 24-28, 2002, Tucson, AZ-pg. 2 In the SSPA two types of analyses of the performance of the potential repository were conducted using the TSPA model. First, a set of "one-off" sensitivity analyses was conducted to evaluate the effects of incorporating the updated models and representations one at a time. Then, the updated models and representations were abstracted and aggregated to produce a modified TSPA model, referred to as the supplemental TSPA model, which captures the combined effects of those alternative representations. This supplemental TSPA model was used to evaluate system performance over a range of thermal operating modes. The supplemental TSPA model results were compared with results of the TSPA-SR to provide insights into the cumulative effects of all model changes on the system results and to demonstrate that the TSPA-SR analyses were conservative in nature, i.e., that a safety margin had been built into the suite of TSPA-SR models

Implementation of Localized Corrosion in the Performance Assessment Model for Yucca Mountain

A total system performance assessment (TSPA) model has been developed to analyze the ability of the natural and engineered barriers of the Yucca Mountain repository to isolate nuclear waste over the 10,000-year period following repository closure. The principal features of the engineered barrier system (EBS) are emplacement tunnels (or ''drifts'') containing a two-layer waste package (WP) for waste containment and a titanium drip shield to protect the waste package from seeping water and falling rock, The 20-mm-thick outer shell of the WP is composed of Alloy 22, a highly corrosion-resistant nickel-based alloy. The barrier function of the EBS is to isolate the waste from migrating water. The water and its associated chemical conditions eventually lead to degradation of the waste packages and mobilization of the radionuclides within the packages. There are five possible waste package degradation modes of the Alloy 22: general corrosion, microbially influenced corrosion, stress corrosion cracking, early failure due to manufacturing defects, and localized corrosion. This paper specifically examines the incorporation of the Alloy-22 localized corrosion model into the Yucca Mountain TSPA model, particularly the abstraction and modeling methodology, as well as issues dealing with scaling, spatial variability, uncertainty, and coupling to other sub-models that are part of the total system model

Important Parameters in the Performance of a Potential Repository at Yucca Mountain (TSPA-1995)

A total system performance assessment (TSPA) was conducted to determine how a potential repository at Yucca Mountain would behave. Using the results of this TSPA, regression was done to determine which parameters had the most important effect on the repository performance. These results were consistent with the current conceptual understanding of the repository